A multispecies test of source–sink indicators to prioritize habitat for declining populations

For species at risk of decline or extinction in source–sink systems, sources are an obvious target for habitat protection actions. However, the way in which source habitats are identified and prioritized can reduce the effectiveness of conservation actions. Although sources and sinks are conceptually defined using both demographic and movement criteria, simplifications are often required in systems with limited data. To assess the conservation outcomes of alternative source metrics and resulting prioritizations, we simulated population dynamics and extinction risk for 3 endangered species. Using empirically based habitat population models, we linked habitat maps with measured site‐ or habitat‐specific demographic conditions, movement abilities, and behaviors. We calculated source–sink metrics over a range of periods of data collection and prioritized consistently high‐output sources for conservation. We then tested whether prioritized patches identified the habitats that most affected persistence by removing them and measuring the population response. Conservation decisions based on different source–sink metrics and durations of data collection affected species persistence. Shorter time series obscured the ability of metrics to identify influential habitats, particularly in temporally variable and slowly declining populations. Data‐rich source–sink metrics that included both demography and movement information did not always identify the habitats with the greatest influence on extinction risk. In some declining populations, patch abundance better predicted influential habitats for short‐term regional persistence. Because source–sink metrics (i.e., births minus deaths; births and immigrations minus deaths and emigration) describe net population conditions and cancel out gross population counts, they may not adequately identify influential habitats in declining populations. For many nonequilibrium populations, new metrics that maintain the counts of individual births, deaths, and movement may provide additional insight into habitats that most influence persistence.     

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.     

Species‐level persistence probabilities for recovery and conservation status assessment

Recovery planning for species listed under the U.S. Endangered Species Act has been hampered by a lack of consistency and transparency, which can be improved by implementing a standardized approach for evaluating species status and developing measurable recovery criteria. However, managers lack an assessment method that integrates threat abatement and can be used when demographic data are limited. To help meet these needs, we demonstrated an approach for evaluating species status based on habitat configuration data. We applied 3 established persistence measures (patch occupancy, metapopulation capacity, and proportion of population lost) to compare 2 conservation strategies (critical habitat designated by the U.S. Fish and Wildlife Service and the Forest Service's Carbonate Habitat Management Strategy) and 2 threat scenarios (maximum limestone mining, removal of all habitat in areas with mining claims; minimum mining, removal of habitat only in areas with existing operations and high‐quality ore) against a baseline of existing habitat for 3 federally listed plant species. Protecting all area within the designated critical habitat maintained a similar level (83.9–99.9%) of species persistence as the baseline, whereas maximum mining greatly reduced persistence (0.51–38.4% maintained). The 3 persistence measures provided complementary insights reflecting different aspects of habitat availability (total area, number of patches, patch size, and connectivity). These measures can be used to link recovery criteria developed following the 3 R principles (representation, redundancy, and resilience) to the resulting improvements in species viability. By focusing on amount and distribution of habitat, our method provides a means of assessing the status of data‐poor species to inform decision making under the Endangered Species Act.     

Conservation Implications of Drastic Reductions in the Smallest and Most Isolated Populations of Giant Pandas

Abstract: In conservation biology, understanding the causes of endangerment is a key step to devising effective conservation strategies. We used molecular evidence (coalescent simulations of population changes from microsatellite data) and historical information (habitat and human population changes) to investigate how the most‐isolated populations of giant pandas (Ailuropoda melanoleuca) in the Xiaoxiangling Mountains became highly endangered. These populations experienced a strong, recent demographic reduction (60‐fold), starting approximately 250 years BP. Explosion of the human population and use of non‐native crop species at the peak of the Qing Empire resulted in land‐use changes, deforestation, and habitat fragmentation, which are likely to have led to the drastic reduction of the most‐isolated populations of giant pandas. We predict that demographic, genetic, and environmental factors will lead to extinction of giant pandas in the Xiaoxiangling Mountains in the future if the population remains isolated. Therefore, a targeted conservation action—translocation—has been proposed and is being implemented by the Chinese goverment.     

Erosion of Heterozygosity in Fluctuating Populations

Abstract: Demographic, environmental, and genetic stochasticity threaten the persistence of isolated populations. The relative importance of these intertwining factors remains unresolved, but a common view is that random demographic and environmental events will usually drive small populations to the brink of extinction before genetic deterioration poses a serious threat. To evaluate the potential importance of genetic factors, we analyzed a model linking demographic and environmental conditions to the loss of genetic diversity in isolated populations undergoing natural levels of fluctuation. Nongenetic processes—environmental stochasticity and population demography—were modeled according to a bounded diffusion process. Genetic processes were modeled by quantifying the rate of drift according to the effective population size, which was predicted from the same parameters used to describe the nongenetic processes. We combined these models to predict the heterozygosity remaining at the time of extinction, as predicted by the nongenetic portion of the model. Our model predicts that many populations will lose most or all of their neutral genetic diversity before nongenetic random events lead to extinction. Given the abundant evidence for inbreeding depression and recent evidence for elevated extinction rates of inbred populations, our findings suggest that inbreeding may be a greater general threat to population persistence than is generally recognized. Therefore, conservation biologists should not ignore the genetic component of extinction risk when assessing species endangerment and developing recovery plans.     

Setting conservation priorities for migratory networks under uncertainty

Conserving migratory species requires protecting connected habitat along the pathways they travel. Despite recent improvements in tracking animal movements, migratory connectivity remains poorly resolved at a population level for the vast majority of species, thus conservation prioritization is hampered. To address this data limitation, we developed a novel approach to spatial prioritization based on a model of potential connectivity derived from empirical data on species abundance and distance traveled between sites during migration. We applied the approach to migratory shorebirds of the East Asian‐Australasian Flyway. Conservation strategies that prioritized sites based on connectivity and abundance metrics together maintained larger populations of birds than strategies that prioritized sites based only on abundance metrics. The conservation value of a site therefore depended on both its capacity to support migratory animals and its position within the migratory pathway; the loss of crucial sites led to partial or total population collapse. We suggest that conservation approaches that prioritize sites supporting large populations of migrants should, where possible, also include data on the spatial arrangement of sites.     

Proposed Conservation Landscape for Giant Pandas in the Minshan Mountains,China

Abstract: The giant panda (Ailuropoda melanoleuca), is one of the world's most endangered species. Habitat loss and fragmentation have reduced its numbers, shrunk its distribution, and separated the population into isolated subpopulations. Such isolated, small populations are in danger of extinction due to random demographic factors and inbreeding. We used least‐cost modeling as a systematic approach to incorporate satellite imagery and data on ecological and behavioral parameters of the giant panda collected during more than 10 years of field research to design a conservation landscape for giant pandas in the Minshan Mountains. We identified 8 core habitats and 4 potential linkages that would link core habitats CH3, CH4, and CH5 with core habitats CH6, CH7, and CH8. Establishing and integrating the identified habitats with existing reserves would create an efficient reserve network for giant panda conservation. The core habitats had an average density of 4.9 pandas/100 km² and contained approximately 76.6% of the giant panda population. About 45% of the core habitat (3245.4 km²) existed outside the current nature reserves network. Total estimated core habitat decreased between 30.4 and 44.5% with the addition of residential areas and road networks factored into the model. A conservation area for giant panda in the Minshan Mountains should aim to ensure habitat retention and connectivity, improve dispersal potential of corridors, and maintain the evolutionary potential of giant pandas in the face of future environmental changes.     

Modeling biodiversity dynamics in countryside landscapes

The future of biodiversity hinges to a great extent on the conservation value of countryside, the growing fraction of Earth's surface heavily influenced by human activities. How many species, and which species, can persist in such landscapes (and analogous seascapes) are open questions. Here we explore two complementary theoretical frameworks to address these questions: species-area relationships and demographic models. We use the terrestrial mammal fauna of Central America to illustrate the application of both frameworks. We begin by proposing a multi-habitat species-area relationship, the countryside species-area relationship, to forecast species extinction rates. To apply it, we classify the mammal fauna by affinity to native and human-dominated habitats. We show how considering the conservation value of countryside habitats changes estimates derived from the classic species-area approach We also examine how the z value of the species-area relationship affects extinction estimates. Next, we present a framework for assessing the relative vulnerability of species to extinction in the countryside, based on the Skellam model of population dynamics. This model predicts the minimum area of contiguous native habitat required for persistence of a species, which we use as an indicator of vulnerability to habitat change. To apply the model, we use our habitat affinity classification of mammals and we estimate life-history parameters by species and habitat type. The resulting ranking of vulnerabilities is significantly correlated with the World Conservation Union (IUCN) Red List assessment.     

Consequences of ignoring dispersal variation in network models for landscape connectivity

Habitat loss and fragmentation can negatively influence population persistence and biodiversity, but the effects can be mitigated if species successfully disperse between isolated habitat patches. Network models are the primary tool for quantifying landscape connectivity, yet in practice, an overly simplistic view of species dispersal is applied. These models often ignore individual variation in dispersal ability under the assumption that all individuals move the same fixed distance with equal probability. We developed a modeling approach to address this problem. We incorporated dispersal kernels into network models to determine how individual variation in dispersal alters understanding of landscape-level connectivity and implemented our approach on a fragmented grassland landscape in Minnesota. Ignoring dispersal variation consistently overestimated a population's robustness to local extinctions and underestimated its robustness to local habitat loss. Furthermore, a simplified view of dispersal underestimated the amount of habitat substructure for small populations but overestimated habitat substructure for large populations. Our results demonstrate that considering biologically realistic dispersal alters understanding of landscape connectivity in ecological theory and conservation practice.     

Demographic Consequences of Terrestrial Habitat Loss for Pool‐Breeding Amphibians: Predicting Extinction Risks Associated with Inadequate Size of Buffer Zones

Abstract: Much of the biodiversity associated with isolated wetlands requires aquatic and terrestrial habitat to maintain viable populations. Current federal wetland regulations in the United States do not protect isolated wetlands or extend protection to surrounding terrestrial habitat. Consequently, some land managers, city planners, and policy makers at the state and local levels are making an effort to protect these wetland and neighboring upland habitats. Balancing human land‐use and habitat conservation is challenging, and well‐informed land‐use policy is hindered by a lack of knowledge of the specific risks of varying amounts of habitat loss. Using projections of wood frog (Rana sylvatica) and spotted salamander (Ambystoma maculatum) populations, we related the amount of high‐quality terrestrial habitat surrounding isolated wetlands to the decline and risk of extinction of local amphibian populations. These simulations showed that current state‐level wetland regulations protecting 30 m or less of surrounding terrestrial habitat are inadequate to support viable populations of pool‐breeding amphibians. We also found that species with different life‐history strategies responded differently to the loss and degradation of terrestrial habitat. The wood frog, with a short life span and high fecundity, was most sensitive to habitat loss and isolation, whereas the longer‐lived spotted salamander with lower fecundity was most sensitive to habitat degradation that lowered adult survival rates. Our model results demonstrate that a high probability of local amphibian population persistence requires sufficient terrestrial habitat, the maintenance of habitat quality, and connectivity among local populations. Our results emphasize the essential role of adequate terrestrial habitat to the maintenance of wetland biodiversity and ecosystem function and offer a means of quantifying the risks associated with terrestrial habitat loss and degradation.     

Quantifying the impact of vegetation-based metrics on species persistence when choosing offsets for habitat destruction

Developers are often required by law to offset environmental impacts through targeted conservation actions. Most offset policies specify metrics for calculating offset requirements, usually by assessing vegetation condition. Despite widespread use, there is little evidence to support the effectiveness of vegetation-based metrics for ensuring biodiversity persistence. We compared long-term impacts of biodiversity offsetting based on area only; vegetation condition only; area × habitat suitability; and condition × habitat suitability in development and restoration simulations for the Hunter Region of New South Wales, Australia. We simulated development and subsequent offsetting through restoration within a virtual landscape, linking simulations to population viability models for 3 species. Habitat gains did not ensure species persistence. No net loss was achieved when performance of offsetting was assessed in terms of amount of habitat restored, but not when outcomes were assessed in terms of persistence. Maintenance of persistence occurred more often when impacts were avoided, giving further support to better enforce the avoidance stage of the mitigation hierarchy. When development affected areas of high habitat quality for species, persistence could not be guaranteed. Therefore, species must be more explicitly accounted for in offsets, rather than just vegetation or habitat alone. Declines due to a failure to account directly for species population dynamics and connectivity overshadowed the benefits delivered by producing large areas of high-quality habitat. Our modeling framework showed that the benefits delivered by offsets are species specific and that simple vegetation-based metrics can give misguided impressions on how well biodiversity offsets achieve no net loss.     

Using Wildlife Communities to Improve Vegetation Classification for Conserving Biodiversity

Determining which vegetation types organisms perceive similarly and classifying these types into groups that function as similar habitats are necessary steps toward expanding the focus of conservation strategies from single species to ecosystems. Therefore, the methods used to determine these habitat classifications are crucial to the successful design and implementation of these conservation strategies. Typically, this process has been accomplished through best professional judgement. We used quantitative techniques to group vegetation types into habitats based on the occurrence of breeding wildlife species ( n = 420) in Oregon. After calculating faunal similarities among all regional vegetation types ( n = 130), we used cluster analysis to group vegetation types into wildlife habitats. We classified the original 130 vegetation types into 30 wildlife habitat types that we believe function similarly. We tested this classification to assess whether vegetation types could be correctly classified into habitat types based on wildlife species composition. Discriminant analysis correctly classified 95% of the vegetation types into their wildlife habitat types, strengthening our confidence in this approach. This approach for classifying habitat types allows consistent development of conservation strategies at coarse resolutions and aids in identifying vegetation types where additional biodiversity surveys are needed. Finally, this approach can be refined continuously as the precision of vegetation mapping and our understanding of organism-habitat associations improve.     

Evaluating tributary restoration potential for Pacific salmon recovery.

Although habitat restoration can play a key role in the conservation of imperiled species, for animals that demonstrate long migrations and complex life histories, reliance on physical restoration of isolated habitat patches comes with considerable uncertainty. Nevertheless, within freshwater ecosystems, stream restoration has become a major conservation focus, with millions of dollars spent annually on efforts aimed at recovering degraded habitat and imperiled riverine species. Within this context, we addressed fundamental uncertainties of the focus on tributary restoration for recovery of salmon: (1) Is there potential for improving habitat in tributaries? (2) What magnitude of early survival improvement can be expected based on stream restoration? and (3) Will incremental increases in early survival be sufficient to ensure viability overall? We combined simple mechanistic habitat models, population viability measures, and categorical filters to quantify "restoration potential," expressed as increased total life-cycle survival in response to restored tributary condition, across 32 populations composing five major population groups (MPG). A wide gap remains between how much survival improvement is needed vs. what is likely to occur; restoration potential meets the necessary minimum increase needed for only four populations within one MPG. The remaining populations (84%, 4 MPG) still fall far below the survival increase needed for future viability. In addition, across all populations and groups, a 171% increase (on average) in total life-cycle survival is needed; only approximately 106% appears possible. A recovery strategy for these salmon that relies largely on tributary restoration to mitigate for known mortality imposed at other life stages (e.g., migration through hydropower dams) is risky with a low probability of success. We demonstrate an approach for completing an a priori evaluation of restoration potential linked to population viability, such that habitat restoration efforts can be biologically prioritized and scarce resources can be allocated to efforts with the greatest potential and the least amount of risk, in terms of meeting conservation and recovery goals.     

Multispecies genetic objectives in spatial conservation planning

Growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision making. Yet, there is no clear‐cut guidance on how genetic features can be incorporated into conservation‐planning processes, despite multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns differ between species, but the potential tradeoffs among genetic objectives for multiple species in conservation planning are currently understudied. We compared spatial conservation prioritizations derived from 2 metrics of genetic diversity (nucleotide and haplotype diversity) and 2 metrics of genetic isolation (private haplotypes and local genetic differentiation) in mitochondrial DNA of 5 marine species. We compared outcomes of conservation plans based only on habitat representation with plans based on genetic data and habitat representation. Fewer priority areas were selected for conservation plans based solely on habitat representation than on plans that included habitat and genetic data. All 4 genetic metrics selected approximately similar conservation‐priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, our results suggest that multispecies genetic conservation objectives are vital to creating protected‐area networks that appropriately preserve community‐level evolutionary patterns.     

Conservation of Species in Dynamic Landscapes: Divergent Fates of Silene tatarica Populations in Riparian Habitats

Abstract:  In transient environments, where local extinctions occur as a result of destruction or deterioration of the local habitat, the long-term persistence of a species requires successful colonizations at new, suitable sites. This kind of habitat tracking should be associated with the asynchronous dynamics of local populations, and it can be especially important for the conservation of rare plant species in riparian habitats. We determined spatiotemporal variation in the demography of the perennial Silene tatarica (L.) Pers. in 15 populations (1998–2003) located in periodically disturbed riparian habitats. The habitats differed according to their morphology (flat shores, slopes) and the amount of bare ground (open, intermediate, closed) along a successional gradient. We used elasticity and life-table response analyses and stochastic simulations to study the variation in population demography. Finite population growth rate was higher in intermediate habitats than in open and closed habitats. In stochastic simulations population size increased in most cases, but four populations were projected to become extinct within 12–70 years. The viability of local populations depended most on the survival and growth of juvenile individuals and on the fecundity of large fertile individuals. On a regional scale, the persistence of this species will require a viable network of local populations as protection against local extinctions caused by natural disturbances and succession. Accordingly, the long-term persistence of riparian species may depend on habitat changes; thus, their conservation requires maintenance of natural disturbance dynamics. Along regulated rivers, management activities such as the creation of open habitats for new colonization should be implemented. Similarly, these activities can be rather general requirements for the conservation of endangered species dependent on transient habitats along successional gradients.     

Integrating functional connectivity and fire management for better conservation outcomes

Globally, the mean abundance of terrestrial animals has fallen by 50% since 1970, and populations face ongoing threats associated with habitat loss, fragmentation, climate change, and disturbance. Climate change can influence the quality of remaining habitat directly and indirectly by precipitating increases in the extent, frequency, and severity of natural disturbances, such as fire. Species face the combined threats of habitat clearance, changing climates, and altered disturbance regimes, each of which may interact and have cascading impacts on animal populations. Typically, conservation agencies are limited in their capacity to mitigate rates of habitat clearance, habitat fragmentation, or climate change, yet fire management is increasingly used worldwide to reduce wildfire risk and achieve conservation outcomes. A popular approach to ecological fire management involves the creation of fire mosaics to promote animal diversity. However, this strategy has 2 fundamental limitations: the effect of fire on animal movement within or among habitat patches is not considered and the implications of the current fire regime for long-term population persistence are overlooked. Spatial and temporal patterns in fire history can influence animal movement, which is essential to the survival of individual animals, maintenance of genetic diversity, and persistence of populations, species, and ecosystems. We argue that there is rich potential for fire managers to manipulate animal movement patterns; enhance functional connectivity, gene flow, and genetic diversity; and increase the capacity of populations to persist under shifting environmental conditions. Recent methodological advances, such as spatiotemporal connectivity modeling, spatially explicit individual-based simulation, and fire-regime modeling can be integrated to achieve better outcomes for biodiversity in human-modified, fire-prone landscapes. Article impact statement: Land managers may conserve populations by using fire to sustain or enhance functional connectivity.     

Demographic Limitations of the Ability of Habitat Restoration to Rescue Declining Populations

Abstract:  Habitat restoration is often recommended in conservation without first evaluating whether populations are in fact habitat limited and thus whether declining populations can be stabilized or recovered through habitat restoration. We used a spatially structured demographic model coupled with a dynamic neutral landscape model to evaluate whether habitat restoration could rescue populations of several generic migratory songbirds that differed in their sensitivity to habitat fragmentation (i.e., severity of edge effects on nesting success). Simulating a best-case scenario, landscapes were instantly restored to 100% habitat before, at, or after habitat loss exceeded the species' vulnerability threshold. The vulnerability threshold is a measure of extinction risk, in which the change in population growth rate ( δλ ) scaled to the rate of habitat loss ( δh ) falls below −1% ( δλ/δh ≤ −0.01). Habitat restoration was most effective for species with low-to-moderate edge sensitivities and in landscapes that had not previously experienced extensive fragmentation. To stabilize populations of species that were highly edge sensitive or any species in heavily fragmented landscapes, restoration needed to be initiated long before the vulnerability threshold was reached. In practice, habitat restoration is generally not initiated until a population is at risk of extinction, but our model results demonstrate that some populations cannot be recovered at this point through habitat restoration alone. At this stage, habitat loss and fragmentation have seriously eroded the species' demographic potential such that halting population declines is limited more by demographic factors than the amount of available habitat. Evidence that populations decline in response to habitat loss is thus not sufficient to conclude that habitat restoration will be sufficient to rescue declining populations.     

Landscape evaluation in conservation: molecular sampling and habitat modeling for the Iberian lynx.

Conservation of endangered species requires comprehensive understanding of their distribution and habitat requirements, in order to implement better management strategies. Unfortunately, this understanding is often difficult to gather at the short term required by rapidly declining populations of many rare vertebrates. We present a spatial habitat modeling approach that integrates a molecular technique for species detection with landscape information to assess habitat requirements of a critically endangered mammalian carnivore, the Iberian lynx (Lynx pardinus), in a poorly known population in Spain. We formulated a set of model hypotheses for habitat selection at the spatial scale of home ranges, based on previous information on lynx requirements of space, vegetation, and prey. To obtain the required data for model selection, we designed a sampling protocol based on surveys of feces and their molecular analysis for species identification. After comparing candidate models, we selected a parsimonious one that allowed (1) reliable assessment of lynx habitat requirements at the scale of home ranges, (2) prediction of lynx distribution and potential population size, and (3) identification of landscape management priorities for habitat conservation. This model predicted that the species was more likely to occur in landscapes with a higher percentage of rocky areas and higher cover of bushes typical of mature mediterranean shrubland mosaics. Its accuracy for discriminating lynx presence was approximately 85%, indicating high predictive performance. Mapping model predictions showed that only 16% of the studied areas constitute potential habitat for lynx, even though the region is dominated by large extents of well-preserved native vegetation with low human interference. Habitat was mostly clumped in two nearby patches connected by vegetation adequate for lynx dispersal and had a capacity for 28-62 potential breeding territories. The lynx population in Sierra Morena is probably the largest persisting today, but it is still critically small for optimism about its long-term persistence. Model results suggest habitat conservation and restoration actions needed for preserving the species, including reconciliation of hunting management with preservation of mature shrubland over large areas (particularly in rocky landscapes). The approach presented here can be applied to many other species for which the ecological information needed to develop sound habitat conservation strategies is lacking.     

Accounting for adaptive capacity and uncertainty in assessments of species’ climate‐change vulnerability

Climate‐change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. We took a more comprehensive approach that incorporates exposure, sensitivity, and capacity to adapt to climate change. We applied our approach to anadromous steelhead trout (Oncorhynchus mykiss) and nonanadromous bull trout (Salvelinus confluentus), threatened salmonids within the Columbia River Basin (U.S.A.). We quantified exposure on the basis of scenarios of future stream temperature and flow, and we represented sensitivity and capacity to adapt to climate change with metrics of habitat quality, demographic condition, and genetic diversity. Both species were found to be highly vulnerable to climate change at low elevations and in their southernmost habitats. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the 2 species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multispecies conservation. Based on our results, we suggest that CCVAs be considered within a broader conceptual and computational framework and be used to refine hypotheses, guide research, and compare plausible scenarios of species’ vulnerability to climate change.